Daniel Wilson

This article examines life assurance and the politics of ‘big data’ in mid-19th-century Britain. The datasets generated by life assurance companies were vast archives of information about human longevity. Actuaries distilled these archives into mortality tables – immensely valuable tools for predicting mortality and so pricing risk. The status of the mortality table was ambiguous, being both a public and a private object: often computed from company records they could also be extrapolated from public projects such as the census, or clerical records. Life assurance more generally straddled the line between private enterprise and collective endeavour, though its advocates stressed the public interest in its success. Reforming actuaries such as Thomas Rowe Edmonds wanted the data on which mortality tables were based to be made publicly available, but faced resistance. Such resistance undermined insurers’ claims to be scientific in spirit and hindered Edmonds’s personal quest for a law of mortality. Edmonds pushed instead for an open actuarial science alongside fellow travellers at the Statistical Society of London, which was populated by statisticians such as William Farr (whose subsequent work, it is argued, was influenced by Edmonds) as well as by radical mathematicians such as Charles Babbage. The article explores Babbage’s little-known foray into the world of insurance, both as a budding actuary but also as a fierce critic of the industry. These debates over the construction, ownership, and accessibility of insurance datasets show that concern about the politics of big data did not begin in the 21st century.

Epidemiology is a science of disease which specifies rates (illness prevalences, incidences, distributions, etc.). Evolution is a science of life which specifies changes (gene frequencies, generations, forms, function, etc.). Evolutionary Epidemiology is a synthesis of these two sciences which combines the empirical power of classical methods in genetical epidemiology with the interpretive capacities of neo-darwinian evolutionary genetics. In particular, prevalence rates of genetical diseases are important data points when reformulated for the purpose of analysis in terms of their evolutionary frequencies. Traits which exceedprevalences beyond the rates of mutation (in Hardy-Weinberg calculations) or evidence unusualrange of phenotypic reaction are of special interest. This is because traits which did not confer advantages in the environment of evolutionary adaptation cannot accede, through natural selection, to anything but low rates of genomic prevalence.Evolutionary epidemiology is, in all of medicine, of particular promise in ongoing efforts to better understand psychopathology. Many complexities of phenotypic adjustment arise when new developmental demands are placed on an old genome. The new and complex biosocial ecology of human mass society now evokes different phenotypes than those in the prehistorical ecology to which the genome is structurally and functionally better adapted. Some of these new phenotypes are darwinian failures. In this paper, the theoretical implications of evolutionary epidemiology are extended and some tentative points of clinical application (particularly to psychiatry) are offered.

Epidemiology is a science of disease which specifies rates . Evolution is a science of life which specifies changes . ‘Evolutionary Epidemiology’ is a synthesis of these two sciences which combines the empirical power of classical methods in genetical epidemiology with the interpretive capacities of neo-darwinian evolutionary genetics. In particular, prevalence rates of genetical diseases are important data points when reformulated for the purpose of analysis in terms of their evolutionary frequencies. Traits which exceedprevalences beyond the rates of mutation or evidence unusualrange of phenotypic reaction are of special interest. This is because traits which did not confer advantages in the environment of evolutionary adaptation cannot accede, through natural selection, to anything but low rates of genomic prevalence.Evolutionary epidemiology is, in all of medicine, of particular promise in ongoing efforts to better understand psychopathology. Many complexities of phenotypic adjustment arise when new developmental demands are placed on an ‘old’ genome. The new and complex biosocial ecology of human mass society now evokes different phenotypes than those in the prehistorical ecology to which the genome is structurally and functionally better adapted. Some of these new phenotypes are darwinian failures. In this paper, the theoretical implications of evolutionary epidemiology are extended and some tentative points of clinical application are offered

The paper offers contextual and integrating comments about sex, evolution and psychopathology as a point of departure toward a new and more scientific understanding of human neurosis. The evolved roots of neurotic behavior are firmly linked to theorems of evolution, which is emerging as the basic science of psychopathology. Evolutionary tenets serve to: 1) redefine key aspects of neuroses, 2) place neurotic behavior in a broad and integrated evolutionary context, and 3) pose basic questions for all psychopathology. Readers who wish to expand, clarify or confirm elements of might well consult basic books in either field as a passing familiarity with psychiatry and biology is assumed.